Senior / Lead Platform Forward Deployed Engineer - Cogentiq I2C

Role overview

Senior / Lead Platform Forward Deployed Engineer - Cogentiq I2C at Fractal

Own the deployment architecture of client installations from environment readiness through hypercare: bundle strategy, environment topology (Dev, QA, production; per-client catalogs), release sequencing, and sign-off that the installation meets the validation standard.

Why this role, now

Responsibilities

• Navigate Unity Catalog and platform governance Client and internal IT control catalog and metastore provisioning, storage decisions, and access models.
• You will assess what their governance model means for our setup scripts, negotiate provisioning paths, and know when a shared-infrastructure convenience creates an SOW, NDA, or data-isolation problem that must be escalated rather than worked around.
• Set and enforce the platform engineering standards: idempotent, rerunnable deployments; fail-fast error handling with no silent except-and-continue paths; environment-variable-driven parameterisation with a single point of change per client value; and configuration conventions that hold across Databricks today and Fabric tomorrow.
• Own the shared utilities architecture: interface-function contracts and factory-pattern abstractions across Databricks, Fabric, PostgreSQL, SQL Server, and storage back ends, packaged as versioned wheel files through Azure Artifactory, so swapping a client's platform is a configuration change, not a rewrite.
• Make the hard ingestion calls: auto-loader versus custom conflict-driven ingestion when the client will not provision Databricks, checkpoint and reprocessing strategy, retry and alerting design per pipeline, and writeback reliability to the application database.
• Run incident command during deployment and hypercare.
• When a deployment breaks in a client environment, you run the incident: triage across the data estate, the application database, and upstream ERP feeds; communicate honestly with the client; and land the fix and the post-incident correction to the playbook.
• Own the deployment playbook as a product.
• The quick-start guides, validation suites, and synthetic data configurations you leave behind must make the next deployment cheaper.
• The bar is that a newcomer deploys the platform from your playbook with one setup script.
• Coach junior Platform FDEs, reviewing their work against the standards you set and growing them toward deployment ownership.

Required qualifications

• 6 or more years in data platform or deployment engineering, with at least two years deploying into environments you did not control (client tenancies, regulated environments, or equivalent).
• Deep Azure Databricks: Asset Bundles, workflows, Unity Catalog and metastore governance, cluster and library management, service-principal automation, and the CLI.
• Strong Python and SQL, with the judgement to review pipeline code for idempotency, failure behaviour, and configuration hygiene, not just correctness.
• PostgreSQL in production: schema evolution, write reliability, connection behaviour under load.
• CI/CD for data platforms: Git-based release flows, semantic versioning, artefact repositories, and backward compatibility across component versions.
• Domain literacy in order-to-cash and accounts receivable data: invoices, receipts, remittances, customer masters, and ERP AR structures in Dynamics 365 or SAP.
• You cannot validate a deployment whose data you do not understand.
• Client-facing composure: you will be the technical face of the deployment to client IT and finance stakeholders.

Preferred qualifications and skills

• Microsoft Fabric, observability design (OpenTelemetry, Application Insights), and experience taking a data product through pilots at multiple clients in parallel.
• Success in the first year
• Two client deployments taken from environment readiness through hypercare, each validated against the standard suite and signed off on schedule.
• A deployment playbook that demonstrably reduced the cost of the deployment that followed it, measured in elapsed time from access granted to validated installation.
• Platform standards (idempotency, fail-fast, parameterisation) adopted across the data engineering codebase, evidenced in review practice, not just documentation.
• At least one governance or infrastructure negotiation with client IT resolved without escalation to leadership.
• If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!
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Employment details

• Location: Bengaluru, Mumbai

Application details

• Cogentiq I2C is Fractal's agentic AI platform for invoice-to-cash operations, spanning Collections, Cash Application, Deductions, Credit Risk, and Invoice Management.
• It owns everything between our release artefacts and a running, observable, correctly governed installation; candidates who want to work on agent behaviour and LLM integration should apply to the AI FDE track instead.

Additional role details

• It's fun to work in a company where people truly BELIEVE in what they are doing!
• We're committed to bringing passion and customer focus to the business.
• About Cogentiq I2C
• The platform runs on a four-tier architecture: a Next.js application layer, FastAPI services, the Cogentiq APA agentic orchestration layer, and a data estate built on Azure Databricks and PostgreSQL.
• Deployments land in client Azure tenancies against live ERP data (Dynamics 365, SAP), which means deployment engineering is a first-class discipline, not an afterthought to development.
• The platform has crossed from being built to being deployed.
• Collections is entering pilot with enterprise clients, and the deployment machinery is real: Databricks Asset Bundles with one-click, script-based deployment; auto-loader ingestion running historical and incremental loads into a common data model; versioned bundles and wheel-file packages delivered through Git and Azure Artifactory; and a quick-start standard under which a newcomer must be able to stand up the full data platform by running one setup script.
• This role carries that machinery into client environments and makes it hold under client governance, client data, and client timelines.